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physiology, data analysis and predictive modelling for the development of decision support tools. This position will also provide ample opportunity for the development of grant and scientific writing skills
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quantitative live-cell imaging to probe and model these processes. By combining stem cell biology with cutting-edge microscopy and physical concepts, we aim to establish a predictive framework for tissue self
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factors: Previous experience in the construction industry; Previous experience in Building Information Modelling; Previous experience in AI and machine learning; Previous experience in process and facility
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data collection and mapping. 3D engineering geological modelling. Within these two areas of activity, the candidate is expected to participate in the following: preparation, collaboration and submission
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and interact. We pioneer new methods for prediction, prevention, diagnostics and treatment of diseases. In the Division of Chemical Biology , we combine and develop protein engineering, synthetic
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, including electronic health records and cohort study data; Develop and apply clustering methods and classification models for patient stratification; Conduct survival analyses and implement time-to-event
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photosynthesis to join the new pilot study of Generative Pretrained Transformer for genomic photosynthesis (GPTgp). The GPTgp project aims to develop a foundational holistic model of photosynthesis that will scale
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system for bacterial genomes using cutting-edge genomic language models. This project aims to adapt and extend transformer-based architectures to create a powerful tool for understanding and predicting
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. The grant may be renewed until the maximum predicted in the project and/or applicable legislation, if it is necessary to complete the academic degree or to carry out activities that are essential
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the JAX Python library, including efficient implementations of classical numerical algorithms. 2. Extend the hybrid FEA-ML framework to include nonlinear cohesive zone models with simple traction separation